The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
The objective of video tracking is to locate a moving object in consecutive video frames. Both the movement of the object and the movement of the video camera can make the imaged object move in the video frame. The tracking requirement of a large number of vision applications can be categorized as tracking in the video stream an object caught by a moving camera in a static scene. For example, in an example scenario of augmented reality, a man with a video camera may point at a static picture having an angry bird in it. The augmented reality module on the device (e.g., a smartphone or a computing tablet) may detect the bird and its sword; then the augmented reality module may overlap a fighting samurai girl upon the detected area. In this example, only the motion of the camera causes the movement of the imaged angry bird. Other examples may include faces of the audience in a meeting room, or an ant crawling on a wall. In these scenes, the impact to the imaging position applied by movement of the object itself is negligible compared to the movement of the video camera.
In a typical prior art method, an object may be located in an image frame by first identifying a target object area in a current image frame, based on the fore knowledge learned in a prior image frame. Thereafter, a search for the object may be launched, moving a search window around a neighborhood encompassing the target object area. However, these kinds of neighborhood search tend to be non-trivial, requiring non-trivial amount of computations and power.